code: def test_0_mean_ensemble(self):
      df = pd.read_csv("tests/data/concrete_strength.csv")
  
      target = "concrete_strength"
  
      json_ai = json_ai_from_problem(
          df,
          ProblemDefinition.from_dict(
              {"target": target, "time_aim": 80}
          ),
      )
  
      json_ai.model = {
          "module": "MeanEnsemble",
          "args": {
              "dtype_dict": "$dtype_dict",
              "submodels": json_ai.model["args"]["submodels"],
          },
      }
  
      code = code_from_json_ai(json_ai)
      predictor = predictor_from_code(code)
      predictor.learn(df)
      predictions = predictor.predict(df)
  
      self.assertTrue(
          r2_score(df[target], predictions["prediction"]) > 0.5
      )
  
file_path: lightwood/tests/integration/basic/test_ensembles.py
imports: import unittest
  import pandas
  from sklearn.metrics import r2_score, accuracy_score
  from lightwood.api.high_level import code_from_json_ai, json_ai_from_problem, predictor_from_code
  from lightwood.api.types import ProblemDefinition
label_desc: Use image node_id 1 for calling the TestBasic obj's underlying member method code with example usage: obj.test_0_mean_ensemble() without return types